On the generation of high dynamic range images : Theory and practice from a statistical perspective

Cecilia Aguerrebere

PhD thesis from Télécom ParisTech, France - 2014

Advisor: Julie Delon

Co-advisor: Yann Gousseau

Research Group(s): No asociado a un grupo (---)

Department(s): (unspecified)

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Resumen

This dissertation studies the problem of high dynamic range (HDR) image
generation from a statistical perspective. A thorough analysis of the camera
acquisition process leads to a simplified yet realistic statistical model describing
raw pixel values. The analysis and methods then proposed are based on
this model.
First, the theoretical performance bound of the problem is computed for the
static case, where the acquisition conditions are controlled. Furthermore, a
new method is proposed that, unlike previous methods, improves the reconstructed
HDR image by taking into account the information carried by saturated
samples.
From a more practical perspective, two methods are proposed to generate
HDR images in the more realistic and complex case where both objects and
camera may exhibit motion. The first one is a multi-image, patch-based
method, that simultaneously estimates and denoises the HDR image. The
other is a single image approach that makes use of a general restoration method
to generate the HDR image. This general restoration method, applicable to a
wide range of problems, constitutes the last contribution of this dissertation.